NDLI: Comparison of three different methods to model the semiconductor manufacturing yield

Content Provider	IEEE Xplore Digital Library
Author	Dupret, Y. Perrin, E. Grolier, J.-L. Kielbasa, R.
Copyright Year	2005
Description	Author affiliation: AItis Semicond., Corbeil-Essonnes (Dupret, Y.; Perrin, E.)
Abstract	During a semiconductor manufacturing process a large amount of data is stored in databases. These data can be used to model the semiconductor manufacturing yield. A model of the yield according to process measurements is useful to predict the yield before final tests. It is also an help to do sensitivity analysis of the yield to process variations. This paper compares three methods to model the manufacturing yield from test data. Principal components analysis, independent component analysis and partial least squares regression are reviewed. A methodology is then exposed to achieve, efficient manufacturing yield modeling
Starting Page	118
Ending Page	123
File Size	826368
Page Count	6
File Format	PDF
ISBN	0780389972
DOI	10.1109/ASMC.2005.1438778
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-04-11
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Virtual manufacturing Semiconductor device manufacture Testing Manufacturing processes Databases Predictive models Sensitivity analysis Pulp manufacturing Principal component analysis Independent component analysis
Content Type	Text
Resource Type	Article

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Comparison of three different methods to model the semiconductor manufacturing yield